The conversion of the construction industry to a circular economy was hindered by several challenges. However, the development of blockchain has shown a promising potential in overcoming these barriers. Nevertheless, there are only limited studies on the dynamics of the system implementation of blockchain-based circulatory management applications within the supply chain for building chains. In this article, a blockchain-based frame for the supply chain for building chains is suggested to promote the circular economy in the construction industry. Systematic evidence synthesis (SES), prototyping and case studies -triangulation approaches are used to check, experiment and validate the results.
Relevant explorative and experimental cases are identified from Scopus and Web of Science databases for the SES process. The first results showed the most important implementation domains and include material passports, waste retail and reverse logistics. Hyperledger and Ethereum are also identified as the leading implementation platforms for the development of prototypes. The most important challenges that were determined from prototype development included, limited simulation samples, limited performance scalability and uncertainty in the return on capital. In order to meet the identified challenges and gaps, a blockchain-based frame for circular building chains (BCCSC) is proposed. Modules from the proposed frame are experimented with a proof-of-concept prototype in order to demonstrate feasibility. Finally, selected cross-indusia cases were triangulated in order to draw conceptual parallels and possible disadvantages when implementing.
Via a blockchain-based web marketplace, stakeholder interactions can be deepened in the building chain's supply chain in order to support circular business models. In addition, the modularization of the frame enables easy scalability and practical implementation. Recommendations for research on cost reduction and improved cooperation strategies as well as the development of modules on a full scale for the detection of end-to-end functions.